## [1] "/Users/zgold/Documents/GitHub/WCOA21"
sample_data %>%
left_join(env_data) %>%
filter(., !is.na(`Sampling method`)) %>%
mutate(`Depth (m)`=as.numeric(`Depth`),
CTDTEMP_ITS90=as.numeric(CTDTEMP_ITS90),
CTDOXY=as.numeric(CTDOXY),
Longitude=as.numeric(Longitude),
Latitude=as.numeric(Latitude)) -> combined
## Joining with `by = join_by(Sample_ID)`
pal <- park_palette("ChannelIslands", 5)
pal2 <- park_palette("Yellowstone", 5)
pal3 <- park_palette("Arches", 5)
pal4 <- park_palette("Hawaii", 5)
combined %>%
ggplot(aes(x=CTDTEMP_ITS90, y=CTDOXY, colour=`Line_ID`)) +geom_count() +scale_color_manual(values=c(pal,pal2,pal3,pal4))
## Warning: Removed 30 rows containing non-finite values (`stat_sum()`).
combined %>%
ggplot(aes(x=Longitude, colour=CTDOXY, y=-log(`Depth (m)`))) +geom_count()+facet_grid(Line_ID~., scales = "free_x")
## Warning: Removed 30 rows containing non-finite values (`stat_sum()`).
## [1] "717"
Vast majority of WCOA samples are taken within the top 100m.
The biological stations are visible here as they are sampled far more frequently.
combined %>%
filter(., Line_ID %in% c("0")) %>%
filter(., Station_ID %in% c("22","23"))%>%
dplyr::select(Station_ID) %>% distinct() -> line_0_to_keep
combined %>%
filter(., Line_ID %in% c("0")) %>%
filter(., `Depth (m)` < 100) %>%
group_by(Longitude,Latitude,Line_ID,Station_ID) %>%
dplyr::summarise(n_depths = n_distinct(`Depth (m)`)) %>%
arrange(Line_ID) -> summed_station_line_0
## `summarise()` has grouped output by 'Longitude', 'Latitude', 'Line_ID'. You can
## override using the `.groups` argument.
ggplot(data = world) +
geom_sf() +
geom_point(data = summed_station_line_0, aes(x = Longitude, y = Latitude,size=n_depths, colour=Line_ID)) +
coord_sf(xlim = c(-126, -123), ylim = c(47, 49), expand = FALSE) +theme_bw() +xlab("Longitude") +ylab("Latitude") +scale_color_manual(values=c(pal,pal2,pal3,pal4)) +
geom_text(data = summed_station_line_0, aes(x = Longitude, y = Latitude, label=Station_ID))
combined %>%
filter(., Line_ID %in% c("2")) %>%
group_by(Longitude,Latitude,Line_ID,Station_ID) %>%
dplyr::summarise(n_depths = n_distinct(`Depth (m)`)) %>%
arrange(Line_ID) -> summed_station_line_2
## `summarise()` has grouped output by 'Longitude', 'Latitude', 'Line_ID'. You can
## override using the `.groups` argument.
ggplot(data = world) +
geom_sf() +
geom_point(data = summed_station_line_2, aes(x = Longitude, y = Latitude, colour=Line_ID)) +
coord_sf(xlim = c(-127, -124), ylim = c(48, 50), expand = FALSE) +theme_bw() +xlab("Longitude") +ylab("Latitude") +scale_color_manual(values=c(pal,pal2,pal3,pal4)) +
geom_text(data = summed_station_line_2, aes(x = Longitude, y = Latitude, label=Station_ID))
combined %>%
filter(., Line_ID %in% c("2")) %>%
filter(., Station_ID %in% c("16","14","12","10","8")) %>%
dplyr::select(Station_ID) %>% distinct() -> line_2_to_keep
combined %>%
filter(., Line_ID %in% c("3")) %>%
group_by(Longitude,Latitude,Line_ID,Station_ID) %>%
dplyr::summarise(n_depths = n_distinct(`Depth (m)`)) %>%
arrange(Line_ID) -> summed_station_line_3
## `summarise()` has grouped output by 'Longitude', 'Latitude', 'Line_ID'. You can
## override using the `.groups` argument.
ggplot(data = world) +
geom_sf() +
geom_point(data = summed_station_line_3, aes(x = Longitude, y = Latitude, colour=Line_ID)) +
coord_sf(xlim = c(-127, -124), ylim = c(46, 50), expand = FALSE) +theme_bw() +xlab("Longitude") +ylab("Latitude") +scale_color_manual(values=c(pal,pal2,pal3,pal4)) +
geom_text(data = summed_station_line_3, aes(x = Longitude, y = Latitude, label=Station_ID))
combined %>%
filter(., Line_ID %in% c("3")) %>%
dplyr::select(Station_ID) %>% distinct() -> line_3_to_keep
combined %>%
filter(., Line_ID %in% c("4")) %>%
group_by(Longitude,Latitude,Line_ID,Station_ID) %>%
dplyr::summarise(n_depths = n_distinct(`Depth (m)`)) %>%
arrange(Line_ID) -> summed_station_line_4
## `summarise()` has grouped output by 'Longitude', 'Latitude', 'Line_ID'. You can
## override using the `.groups` argument.
ggplot(data = world) +
geom_sf() +
geom_point(data = summed_station_line_4, aes(x = Longitude, y = Latitude, colour=Line_ID)) +
coord_sf(xlim = c(-127, -124), ylim = c(46, 48), expand = FALSE) +theme_bw() +xlab("Longitude") +ylab("Latitude") +scale_color_manual(values=c(pal,pal2,pal3,pal4)) +
geom_text(data = summed_station_line_4, aes(x = Longitude, y = Latitude, label=Station_ID))
combined %>%
filter(., Line_ID %in% c("4")) %>%
filter(., Station_ID %in% c("37","40","41","42","43"))%>%
dplyr::select(Station_ID) %>% distinct() -> line_4_to_keep
combined %>%
filter(., Line_ID %in% c("5")) %>%
group_by(Longitude,Latitude,Line_ID,Station_ID) %>%
dplyr::summarise(n_depths = n_distinct(`Depth (m)`)) %>%
arrange(Line_ID) -> summed_station_line_5
## `summarise()` has grouped output by 'Longitude', 'Latitude', 'Line_ID'. You can
## override using the `.groups` argument.
ggplot(data = world) +
geom_sf() +
geom_point(data = summed_station_line_5, aes(x = Longitude, y = Latitude, colour=Line_ID)) +
coord_sf(xlim = c(-126, -123), ylim = c(45, 47), expand = FALSE) +theme_bw() +xlab("Longitude") +ylab("Latitude") +scale_color_manual(values=c(pal,pal2,pal3,pal4)) +
geom_text(data = summed_station_line_5, aes(x = Longitude, y = Latitude, label=Station_ID))
combined %>%
filter(., Line_ID %in% c("5")) %>%
filter(., Station_ID %in% c("30","32","33","34","26"))%>%
dplyr::select(Station_ID) %>% distinct() -> line_5_to_keep
combined %>%
filter(., Line_ID %in% c("6")) %>%
group_by(Longitude,Latitude,Line_ID,Station_ID) %>%
dplyr::summarise(n_depths = n_distinct(`Depth (m)`)) %>%
arrange(Line_ID) -> summed_station_line_6
## `summarise()` has grouped output by 'Longitude', 'Latitude', 'Line_ID'. You can
## override using the `.groups` argument.
ggplot(data = world) +
geom_sf() +
geom_point(data = summed_station_line_6, aes(x = Longitude, y = Latitude, colour=Line_ID)) +
coord_sf(xlim = c(-125.5, -123.5), ylim = c(44, 45), expand = FALSE) +theme_bw() +xlab("Longitude") +ylab("Latitude") +scale_color_manual(values=c(pal,pal2,pal3,pal4)) +
geom_text(data = summed_station_line_6, aes(x = Longitude, y = Latitude, label=Station_ID))
combined %>%
filter(., Line_ID %in% c("6")) %>%
filter(., Station_ID %in% c("47","48","49","50","52"))%>%
dplyr::select(Station_ID) %>% distinct() -> line_6_to_keep
combined %>%
filter(., Line_ID %in% c("7")) %>%
group_by(Longitude,Latitude,Line_ID,Station_ID) %>%
dplyr::summarise(n_depths = n_distinct(`Depth (m)`)) %>%
arrange(Line_ID) -> summed_station_line_7
## `summarise()` has grouped output by 'Longitude', 'Latitude', 'Line_ID'. You can
## override using the `.groups` argument.
ggplot(data = world) +
geom_sf() +
geom_point(data = summed_station_line_7, aes(x = Longitude, y = Latitude, colour=Line_ID)) +
coord_sf(xlim = c(-126, -123.5), ylim = c(43, 44.5), expand = FALSE) +theme_bw() +xlab("Longitude") +ylab("Latitude") +scale_color_manual(values=c(pal,pal2,pal3,pal4)) +
geom_text(data = summed_station_line_7, aes(x = Longitude, y = Latitude, label=Station_ID))
combined %>%
filter(., Line_ID %in% c("7")) %>%
filter(., Station_ID %in% c("54","55","56","57","58"))%>%
dplyr::select(Station_ID) %>% distinct() -> line_7_to_keep
combined %>%
filter(., Line_ID %in% c("8")) %>%
group_by(Longitude,Latitude,Line_ID,Station_ID) %>%
dplyr::summarise(n_depths = n_distinct(`Depth (m)`)) %>%
arrange(Line_ID) -> summed_station_line_8
## `summarise()` has grouped output by 'Longitude', 'Latitude', 'Line_ID'. You can
## override using the `.groups` argument.
ggplot(data = world) +
geom_sf() +
geom_point(data = summed_station_line_8, aes(x = Longitude, y = Latitude, colour=Line_ID)) +
coord_sf(xlim = c(-125.5, -123.5), ylim = c(41.5, 42.5), expand = FALSE) +theme_bw() +xlab("Longitude") +ylab("Latitude") +scale_color_manual(values=c(pal,pal2,pal3,pal4)) +
geom_text(data = summed_station_line_8, aes(x = Longitude, y = Latitude, label=Station_ID))
combined %>%
filter(., Line_ID %in% c("8")) %>%
filter(., Station_ID %in% c("62","63","65","66","67"))%>%
dplyr::select(Station_ID) %>% distinct() -> line_8_to_keep
combined %>%
filter(., Line_ID %in% c("9")) %>%
group_by(Longitude,Latitude,Line_ID,Station_ID) %>%
dplyr::summarise(n_depths = n_distinct(`Depth (m)`)) %>%
arrange(Line_ID) -> summed_station_line_9
## `summarise()` has grouped output by 'Longitude', 'Latitude', 'Line_ID'. You can
## override using the `.groups` argument.
ggplot(data = world) +
geom_sf() +
geom_point(data = summed_station_line_9, aes(x = Longitude, y = Latitude, colour=Line_ID)) +
coord_sf(xlim = c(-125.5, -123.5), ylim = c(39.5, 40.5), expand = FALSE) +theme_bw() +xlab("Longitude") +ylab("Latitude") +scale_color_manual(values=c(pal,pal2,pal3,pal4)) +
geom_text(data = summed_station_line_9, aes(x = Longitude, y = Latitude, label=Station_ID))
combined %>%
filter(., Line_ID %in% c("9")) %>%
filter(., Station_ID %in% c("70","71","72","73","75"))%>%
dplyr::select(Station_ID) %>% distinct() -> line_9_to_keep
combined %>%
filter(., Line_ID %in% c("11")) %>%
group_by(Longitude,Latitude,Line_ID,Station_ID) %>%
dplyr::summarise(n_depths = n_distinct(`Depth (m)`)) %>%
arrange(Line_ID) -> summed_station_line_11
## `summarise()` has grouped output by 'Longitude', 'Latitude', 'Line_ID'. You can
## override using the `.groups` argument.
ggplot(data = world) +
geom_sf() +
geom_point(data = summed_station_line_11, aes(x = Longitude, y = Latitude, colour=Line_ID)) +
coord_sf(xlim = c(-124, -122), ylim = c(37, 39), expand = FALSE) +theme_bw() +xlab("Longitude") +ylab("Latitude") +scale_color_manual(values=c(pal,pal2,pal3,pal4)) +
geom_text(data = summed_station_line_11, aes(x = Longitude, y = Latitude, label=Station_ID))
combined %>%
filter(., Line_ID %in% c("11")) %>%
filter(., Station_ID %in% c("79","81","82","83","84"))%>%
dplyr::select(Station_ID) %>% distinct() -> line_11_to_keep
combined %>%
filter(., Line_ID %in% c("13")) %>%
group_by(Longitude,Latitude,Line_ID,Station_ID) %>%
dplyr::summarise(n_depths = n_distinct(`Depth (m)`)) %>%
arrange(Line_ID) -> summed_station_line_13
## `summarise()` has grouped output by 'Longitude', 'Latitude', 'Line_ID'. You can
## override using the `.groups` argument.
ggplot(data = world) +
geom_sf() +
geom_point(data = summed_station_line_13, aes(x = Longitude, y = Latitude, colour=Line_ID)) +
coord_sf(xlim = c(-124, -121), ylim = c(35.8, 37), expand = FALSE) +theme_bw() +xlab("Longitude") +ylab("Latitude") +scale_color_manual(values=c(pal,pal2,pal3,pal4)) +
geom_text(data = summed_station_line_13, aes(x = Longitude, y = Latitude, label=Station_ID))
combined %>%
filter(., Line_ID %in% c("13")) %>%
filter(., Station_ID %in% c("97","98","101","103"))%>%
dplyr::select(Station_ID) %>% distinct() -> line_13_to_keep
combined %>%
filter(., Line_ID %in% c("14")) %>%
group_by(Longitude,Latitude,Line_ID,Station_ID) %>%
dplyr::summarise(n_depths = n_distinct(`Depth (m)`)) %>%
arrange(Line_ID) -> summed_station_line_14
## `summarise()` has grouped output by 'Longitude', 'Latitude', 'Line_ID'. You can
## override using the `.groups` argument.
ggplot(data = world) +
geom_sf() +
geom_point(data = summed_station_line_14, aes(x = Longitude, y = Latitude, colour=Line_ID)) +
coord_sf(xlim = c(-124, -121), ylim = c(34, 36), expand = FALSE) +theme_bw() +xlab("Longitude") +ylab("Latitude") +scale_color_manual(values=c(pal,pal2,pal3,pal4)) +
geom_text(data = summed_station_line_14, aes(x = Longitude, y = Latitude, label=Station_ID))
combined %>%
filter(., Line_ID %in% c("14"))%>%
filter(., Station_ID %in% c("107","106","105","104"))%>%
dplyr::select(Station_ID) %>% distinct() -> line_14_to_keep
combined %>%
filter(., Line_ID %in% c("15")) %>%
group_by(Longitude,Latitude,Line_ID,Station_ID) %>%
dplyr::summarise(n_depths = n_distinct(`Depth (m)`)) %>%
arrange(Line_ID) -> summed_station_line_15
## `summarise()` has grouped output by 'Longitude', 'Latitude', 'Line_ID'. You can
## override using the `.groups` argument.
ggplot(data = world) +
geom_sf() +
geom_point(data = summed_station_line_15, aes(x = Longitude, y = Latitude, colour=Line_ID)) +
coord_sf(xlim = c(-124, -120), ylim = c(32, 35), expand = FALSE) +theme_bw() +xlab("Longitude") +ylab("Latitude") +scale_color_manual(values=c(pal,pal2,pal3,pal4)) +
geom_text(data = summed_station_line_15, aes(x = Longitude, y = Latitude, label=Station_ID))
combined %>%
filter(., Line_ID %in% c("15")) %>%
filter(., Station_ID %in% c("110","111","113","114","117"))%>%
dplyr::select(Station_ID) %>% distinct() -> line_15_to_keep
combined %>%
filter(., Line_ID %in% c("16")) %>%
group_by(Longitude,Latitude,Line_ID,Station_ID) %>%
dplyr::summarise(n_depths = n_distinct(`Depth (m)`)) %>%
arrange(Line_ID) -> summed_station_line_16
## `summarise()` has grouped output by 'Longitude', 'Latitude', 'Line_ID'. You can
## override using the `.groups` argument.
ggplot(data = world) +
geom_sf() +
geom_point(data = summed_station_line_16, aes(x = Longitude, y = Latitude, colour=Line_ID)) +
coord_sf(xlim = c(-121, -118), ylim = c(33.5, 35), expand = FALSE) +theme_bw() +xlab("Longitude") +ylab("Latitude") +scale_color_manual(values=c(pal,pal2,pal3,pal4)) +
geom_text(data = summed_station_line_16, aes(x = Longitude, y = Latitude, label=Station_ID))
combined %>%
filter(., Line_ID %in% c("16")) %>%
filter(., Station_ID %in% c("118","120","121","122","123"))%>%
dplyr::select(Station_ID) %>% distinct() -> line_16_to_keep
combined %>%
filter(., Line_ID %in% c("17")) %>%
group_by(Longitude,Latitude,Line_ID,Station_ID) %>%
dplyr::summarise(n_depths = n_distinct(`Depth (m)`)) %>%
arrange(Line_ID) -> summed_station_line_17
## `summarise()` has grouped output by 'Longitude', 'Latitude', 'Line_ID'. You can
## override using the `.groups` argument.
ggplot(data = world) +
geom_sf() +
geom_point(data = summed_station_line_17, aes(x = Longitude, y = Latitude, colour=Line_ID)) +
coord_sf(xlim = c(-121, -117), ylim = c(31, 34), expand = FALSE) +theme_bw() +xlab("Longitude") +ylab("Latitude") +scale_color_manual(values=c(pal,pal2,pal3,pal4)) +
geom_text(data = summed_station_line_17, aes(x = Longitude, y = Latitude, label=Station_ID))
combined %>%
filter(., Line_ID %in% c("17")) %>%
filter(., Station_ID %in% c("124","126","127","129","131")) %>%
dplyr::select(Station_ID) %>% distinct() -> line_17_to_keep
combined %>%
filter(., Station_ID %in% c(line_0_to_keep$Station_ID,line_2_to_keep$Station_ID,line_3_to_keep$Station_ID,line_4_to_keep$Station_ID,line_5_to_keep$Station_ID,line_6_to_keep$Station_ID,line_7_to_keep$Station_ID,line_8_to_keep$Station_ID,line_9_to_keep$Station_ID,line_11_to_keep$Station_ID,line_13_to_keep$Station_ID,line_14_to_keep$Station_ID,line_15_to_keep$Station_ID,line_16_to_keep$Station_ID,line_17_to_keep$Station_ID)) -> combined_station_to_keep
combined_station_to_keep %>%
filter(., Line_ID %in% c("6","7")) %>%
filter(., `Depth (m)` > 100) %>%
filter(., Longitude > -125) %>%
group_by(Station_ID,Line_ID) %>%
dplyr::summarise(max_depth = max(`Depth (m)`)) %>%
unite(., "station_line", Station_ID:Line_ID, sep=":", remove=F) -> max_depths_6_7
## `summarise()` has grouped output by 'Station_ID'. You can override using the
## `.groups` argument.
combined_station_to_keep %>%
filter(., Line_ID %in% c("6","7")) %>%
unite(., "station_line", c("Station_ID","Line_ID"), sep=":", remove=F) %>%
filter(., station_line %in% max_depths_6_7$station_line) -> max_depth_to_keep_6_7
combined_station_to_keep %>%
filter(., Line_ID %in% c("6","7")) %>%
ggplot(., aes(x=Longitude, y=-`Depth (m)`))+geom_point() +facet_grid(Station_ID~Line_ID)
combined_station_to_keep %>%
mutate(., to_keep = case_when(Sample_ID %in% max_depth_to_keep_6_7$Sample_ID ~ "keep",
`Depth (m)` < 100 ~ "keep",
TRUE ~"drop")) %>%
filter(., to_keep =="keep") -> samples_to_keep
samples_to_keep %>%
dplyr::summarise(n_distinct(`FINAL Sample NAME`), n_distinct(Sample_ID), n_distinct(`Sequential G3 Sample No.`))
## # A tibble: 1 × 3
## n_distinct(\FINAL Sample NAME\…¹ n_distinct(Sample_ID…² n_distinct(\Sequenti…³
## <int> <int> <int>
## 1 290 281 198
## # ℹ abbreviated names: ¹​`n_distinct(\`FINAL Sample NAME\`)`,
## # ²​`n_distinct(Sample_ID)`, ³​`n_distinct(\`Sequential G3 Sample No.\`)`
ggplot(data = world) +
geom_sf() +
geom_point(data = samples_to_keep, aes(x = Longitude, y = Latitude, colour=Line_ID)) +
coord_sf(xlim = c(-127, -117), ylim = c(31, 50), expand = FALSE) +theme_bw() +xlab("Longitude") +ylab("Latitude") +scale_color_manual(values=c(pal,pal2,pal3,pal4)) +
geom_text(data = samples_to_keep, aes(x = Longitude, y = Latitude, label=Station_ID))
samples_to_keep %>%
ggplot(aes(x=CTDTEMP_ITS90, y=CTDOXY, colour=`Line_ID`)) +geom_count() +scale_color_manual(values=c(pal,pal2,pal3,pal4))
# O2, Temp, Depth
samples_to_keep %>%
mutate(., pH_T_measured = as.numeric(pH_T_measured)) %>%
ggplot(aes(x=CTDTEMP_ITS90, y=CTDOXY, colour=log(`Depth (m)`))) +geom_count()
### Save Selected Samples
write.csv(samples_to_keep, file=here("zacks_suggested_stations_20230418.csv"))